Recent development of risk-prediction models for incident hypertension: An updated systematic review

Background
Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative.
Methods
Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc.
Results
From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%.
Conclusions
The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment.

背景
高血压是全球首要健康威胁，亦是主要心血管疾病。鉴于临床干预可有效延缓高血压前期向高血压的疾病进展，亟需构建可识别高血压高危人群的诊断预测模型。
方法
本研究检索PubMed与Embase数据库，筛选符合纳入标准的高血压预测模型或风险评分相关研究文献。研究收集了涵盖风险因素、统计方法、研究设计与受试者特征、模型性能评估指标在内的多项数据。
结果
经筛选，最终纳入26项研究，共涉及48个高血压预测模型。其中20项研究针对基于传统风险因素的已构建模型展开分析，传统风险因素包括体重指数（Body Mass Index, BMI）、年龄、吸烟史、血压（Blood Pressure, BP）水平、高血压家族史及生化指标；另有6项研究以遗传风险评分（Genetic Risk Score, GRS）作为预测因子。模型的受试者工作特征曲线下面积（AUC）介于0.64至0.97之间，C统计量（C-statistic）范围为60%至90%。
结论
目前基于传统风险因素的模型仍是高血压风险预测的主流模型，但近期已有越来越多的模型将遗传因素纳入预测因子范畴。但此类遗传预测因子需经过严谨筛选。现有已报道的模型均具备可接受至优良的区分度与校准能力，但此类模型能否应用于临床实践，仍需开展更多验证与调整工作。